MétaCan
Menu
Back to cohort
Record W2902681168 · doi:10.1002/msc.1376

Nurse telephone education for promoting a treat‐to‐target approach in recently diagnosed rheumatoid arthritis patients: A pilot project

2018· article· en· W2902681168 on OpenAlexfundno aff
Siobhan Farley, Bonita Libman, Melinda Edwards, Carl J. Possidente, Amanda G. Kennedy

Bibliographic record

VenueMusculoskeletal Care · 2018
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
FundersPfizer Canada
KeywordsMedicineRheumatoid arthritisFamily medicinePatient educationPhysical therapyTelephone interviewRheumatologyNurse practitionersNursingInternal medicineHealth care

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of the present study was to implement a nurse telephone education programme for patients with recently diagnosed rheumatoid arthritis (RA) that promotes shared decision-making and a treat-to-target approach. METHODS: This was a pilot project of newly diagnosed adult RA patients conducted between November 2015 and December 2016. A rheumatology clinic nurse telephoned patients to offer disease education. A toolkit was mailed to patients. Measures included call attempts, call time, a qualitative description of free-text notes and the proportion of patients who adhered to their next clinic visit. Data were analysed descriptively and qualitatively. RESULTS: Twenty-six patients participated in the nurse calls. Most patients were female (65%), with a median age of 54 years (range 22-78 years). Median call length was 14.5 min, with a range of 8-23 min. Qualitative notes indicated that patients overwhelmingly supported the nurse calls. Nineteen patients (73%) were adherent to their follow-up visit. CONCLUSION: This preliminary project successfully implemented an educational programme that included a nurse-facilitated, RA-specific, telephone call and toolkit. This educational programme could be a model for similar educational efforts by other clinics.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.299
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueMusculoskeletal CareSame topicRheumatoid Arthritis Research and TherapiesFrench-language works237,207